Learning User Activities from Energy Demand Profiles
Proc. 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology
, pp. 873–879
(2015)
Abstract:
In this paper, we propose the use of energy load profiles to learn human activities. An energy load profile determines the energy consumption of an appliance during a specific interval of time. We propose the use of clustering techniques to group the different profiles according to their temporal consumption. Both Hard and Soft clustering techniques are evaluated. We have tested the method with data from REMODECE (Residential Monitoring to Decrease Energy Use and Carbon Emissions in Europe) database.
Links:
| DOI: 10.2991/ifsa-eusflat-15.2015.123 PDF: |
Bibtex:
@inproceedings{IFSA2015_Ros,
title = {Learning User Activities from Energy Demand Profiles},
author = {Ros, Maria and Molina-Solana, Miguel and Martin-Bautista, M.J. and Delgado, Miguel and Vila, Amparo},
booktitle = {Proc. 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology},
year = {2015},
address = {Gij\'on, Spain},
editor = {Alonso, Jos\'e M. and Bustince, Humberto and Reformat, Marek},
month = jun,
organization = {European Centre for Soft Computing},
pages = {873--879},
publisher = {Atlantis Press},
doi = {10.2991/ifsa-eusflat-15.2015.123},
timestamp = {119},
url = {http://www.softcomputing.es/ifsa-eusflat2015/}
}